Machine Learning System Design MEAP V03 by copyright-2023-manning-publications.html

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Figure 5.1 Residuals after optimizing the median

When we calculate MSE and MAE for a model with the MAE loss function, the result will be: MSE = 81,000, MAE = 90. With the mean of residuals being equal to -90 and the median of residuals being equal to 0 (Figure 5.2).

Figure 5.2 Residuals after optimizing the mean

No wonder the model optimized for MSE yields better MSE, and as MSE tries to minimize the mean, the better mean residuals. On the other hand, the model optimized for MAE delivers better MAE, and as MAE tries to optimize the median, the better median residuals. But what does it mean for us? Which loss function is better? That depends on our application.

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